State-of-the-art LBS rely on a classical search paradigm that propagates hard filtering with an exact-match semantics, oftentimes leading to flooding or empty results. In this case, users are willing to accept best alternatives, results that are slightly outside of the search radius but satisfy other criteria or results close to the current location with drawbacks concerning non-spatial attributes.
In this talk, Florian Wenzel discusses how the Preference SQL system developed at the Chair for Databases and Information Systems at the University of Augsburg can be efficiently employed in LBS to provide such an alternative soft constraint search paradigm with best-matches-only query semantics.

Florian will also showcase a web-based research prototype that illustrates these search capabilities by finding best-matching results for individuals and groups of users.